{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-05-07T15:08:14.880464Z",
     "start_time": "2025-05-07T15:08:12.163187Z"
    }
   },
   "source": "from modelscope import AutoModelForCausalLM, AutoTokenizer",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\conda\\a311\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-07T15:09:19.903249Z",
     "start_time": "2025-05-07T15:08:14.883931Z"
    }
   },
   "cell_type": "code",
   "source": [
    "model_name = \"unsloth/Qwen3-1.7B-unsloth-bnb-4bit\"\n",
    "model = AutoModelForCausalLM.from_pretrained(model_name)\n",
    "tokenizer = AutoTokenizer.from_pretrained(model_name)"
   ],
   "id": "d00b226256af60a",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-05-07 23:08:15,382 - modelscope - WARNING - Using branch: master as version is unstable, use with caution\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Model from https://www.modelscope.cn to directory: C:\\Users\\51165\\.cache\\modelscope\\hub\\models\\unsloth\\Qwen3-1.7B-unsloth-bnb-4bit\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "2025-05-07 23:09:15,818 - modelscope - INFO - Creating symbolic link [C:\\Users\\51165\\.cache\\modelscope\\hub\\models\\unsloth\\Qwen3-1.7B-unsloth-bnb-4bit].\n",
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     "text": [
      "Downloading Model from https://www.modelscope.cn to directory: C:\\Users\\51165\\.cache\\modelscope\\hub\\models\\unsloth\\Qwen3-1.7B-unsloth-bnb-4bit\n"
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    }
   ],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-07T15:09:30.052401Z",
     "start_time": "2025-05-07T15:09:30.046733Z"
    }
   },
   "cell_type": "code",
   "source": "model",
   "id": "e624ad4a487adeb",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Qwen3ForCausalLM(\n",
       "  (model): Qwen3Model(\n",
       "    (embed_tokens): Embedding(151936, 2048, padding_idx=151654)\n",
       "    (layers): ModuleList(\n",
       "      (0-1): 2 x Qwen3DecoderLayer(\n",
       "        (self_attn): Qwen3Attention(\n",
       "          (q_proj): Linear4bit(in_features=2048, out_features=2048, bias=False)\n",
       "          (k_proj): Linear4bit(in_features=2048, out_features=1024, bias=False)\n",
       "          (v_proj): Linear4bit(in_features=2048, out_features=1024, bias=False)\n",
       "          (o_proj): Linear4bit(in_features=2048, out_features=2048, bias=False)\n",
       "          (q_norm): Qwen3RMSNorm((128,), eps=1e-06)\n",
       "          (k_norm): Qwen3RMSNorm((128,), eps=1e-06)\n",
       "        )\n",
       "        (mlp): Qwen3MLP(\n",
       "          (gate_proj): Linear4bit(in_features=2048, out_features=6144, bias=False)\n",
       "          (up_proj): Linear4bit(in_features=2048, out_features=6144, bias=False)\n",
       "          (down_proj): Linear4bit(in_features=6144, out_features=2048, bias=False)\n",
       "          (act_fn): SiLU()\n",
       "        )\n",
       "        (input_layernorm): Qwen3RMSNorm((2048,), eps=1e-06)\n",
       "        (post_attention_layernorm): Qwen3RMSNorm((2048,), eps=1e-06)\n",
       "      )\n",
       "      (2): Qwen3DecoderLayer(\n",
       "        (self_attn): Qwen3Attention(\n",
       "          (q_proj): Linear4bit(in_features=2048, out_features=2048, bias=False)\n",
       "          (k_proj): Linear4bit(in_features=2048, out_features=1024, bias=False)\n",
       "          (v_proj): Linear4bit(in_features=2048, out_features=1024, bias=False)\n",
       "          (o_proj): Linear4bit(in_features=2048, out_features=2048, bias=False)\n",
       "          (q_norm): Qwen3RMSNorm((128,), eps=1e-06)\n",
       "          (k_norm): Qwen3RMSNorm((128,), eps=1e-06)\n",
       "        )\n",
       "        (mlp): Qwen3MLP(\n",
       "          (gate_proj): Linear(in_features=2048, out_features=6144, bias=False)\n",
       "          (up_proj): Linear(in_features=2048, out_features=6144, bias=False)\n",
       "          (down_proj): Linear(in_features=6144, out_features=2048, bias=False)\n",
       "          (act_fn): SiLU()\n",
       "        )\n",
       "        (input_layernorm): Qwen3RMSNorm((2048,), eps=1e-06)\n",
       "        (post_attention_layernorm): Qwen3RMSNorm((2048,), eps=1e-06)\n",
       "      )\n",
       "      (3-27): 25 x Qwen3DecoderLayer(\n",
       "        (self_attn): Qwen3Attention(\n",
       "          (q_proj): Linear4bit(in_features=2048, out_features=2048, bias=False)\n",
       "          (k_proj): Linear4bit(in_features=2048, out_features=1024, bias=False)\n",
       "          (v_proj): Linear4bit(in_features=2048, out_features=1024, bias=False)\n",
       "          (o_proj): Linear4bit(in_features=2048, out_features=2048, bias=False)\n",
       "          (q_norm): Qwen3RMSNorm((128,), eps=1e-06)\n",
       "          (k_norm): Qwen3RMSNorm((128,), eps=1e-06)\n",
       "        )\n",
       "        (mlp): Qwen3MLP(\n",
       "          (gate_proj): Linear4bit(in_features=2048, out_features=6144, bias=False)\n",
       "          (up_proj): Linear4bit(in_features=2048, out_features=6144, bias=False)\n",
       "          (down_proj): Linear4bit(in_features=6144, out_features=2048, bias=False)\n",
       "          (act_fn): SiLU()\n",
       "        )\n",
       "        (input_layernorm): Qwen3RMSNorm((2048,), eps=1e-06)\n",
       "        (post_attention_layernorm): Qwen3RMSNorm((2048,), eps=1e-06)\n",
       "      )\n",
       "    )\n",
       "    (norm): Qwen3RMSNorm((2048,), eps=1e-06)\n",
       "    (rotary_emb): Qwen3RotaryEmbedding()\n",
       "  )\n",
       "  (lm_head): Linear(in_features=2048, out_features=151936, bias=False)\n",
       ")"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-05-07T15:09:30.111661Z",
     "start_time": "2025-05-07T15:09:30.108760Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "36fd186aadb259a",
   "outputs": [],
   "execution_count": null
  }
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